2 citations · 2 across the 3 of their papers we have counts for
10 papers
Algorithmic Probability-guided Supervised Machine Learning on Non-differentiable Spaces
Santiago Hernández-Orozco, Hector Zenil, Jürgen Riedel +3
We show how complexity theory can be introduced in machine learning to help bring together apparently disparate areas of current research. We show that this new approach requires l…
Estimations of Integrated Information Based on Algorithmic Complexity and Dynamic Querying
Alberto Hernández-Espinosa, Héctor Zenil, Narsis A. Kiani +1
The concept of information has emerged as a language in its own right, bridging several disciplines that analyze natural phenomena and man-made systems. Integrated information has…
Controllability, Multiplexing, and Transfer Learning in Networks using Evolutionary Learning
Rise Ooi, Chao-Han Huck Yang, Pin-Yu Chen +5
Networks are fundamental building blocks for representing data, and computations. Remarkable progress in learning in structurally defined (shallow or deep) networks has recently be…
The Thermodynamics of Network Coding, and an Algorithmic Refinement of the Principle of Maximum Entropy
Hector Zenil, Narsis A. Kiani, Jesper Tegnér
The principle of maximum entropy (Maxent) is often used to obtain prior probability distributions as a method to obtain a Gibbs measure under some restriction giving the probabilit…
Algorithmic Complexity and Reprogrammability of Chemical Structure Networks
Hector Zenil, Narsis A. Kiani, Ming-Mei Shang +1
Here we address the challenge of profiling causal properties and tracking the transformation of chemical compounds from an algorithmic perspective. We explore the potential of appl…
Symmetry and Algorithmic Complexity of Polyominoes and Polyhedral Graphs
Hector Zenil, Narsis A. Kiani, Jesper Tegnér
We introduce a definition of algorithmic symmetry able to capture essential aspects of geometric symmetry. We review, study and apply a method for approximating the algorithmic com…